Antenna Pattern Exploration Data
Explore data related to antenna pattern exploration, including Wiener Filter application, Wiener-Hopf equation, witness channel data, waveform injections, and data analysis of Dimmelmeier and Murphy catalogs.
Uploaded on | 0 Views
Download Presentation
Please find below an Image/Link to download the presentation.
The content on the website is provided AS IS for your information and personal use only. It may not be sold, licensed, or shared on other websites without obtaining consent from the author. If you encounter any issues during the download, it is possible that the publisher has removed the file from their server.
You are allowed to download the files provided on this website for personal or commercial use, subject to the condition that they are used lawfully. All files are the property of their respective owners.
The content on the website is provided AS IS for your information and personal use only. It may not be sold, licensed, or shared on other websites without obtaining consent from the author.
E N D
Presentation Transcript
SMEE Project Update Vincent Roma 2016
Wiener Filter Filter applied through convolution in the time domain. Target data: y(k) with N samples Witness data: x(k) Our filter: f(l) with L + 1 coefficients E represents the mean square error between target data and predicted data. Create our filter by minimizing the mean square error. That means setting derivative with respect to each filter coefficient to zero. 3
Derivative constraints lead to the Wiener- Hopf equation. Rxx is auto-correlation matrix of witness data, x(k) where k = [0,..., L] cyx is cross-correlation matrix between witness and target data. Signals are real so the auto-correlation matrix is symmetric, resulting in a Toeplitz structured system of equations. Solution obtained with the Levinson-Durbin algorithm. Output data, r(k), is predicted data subtracted from target data. 4
Witness Channel: H1:IMC-WFS_B_I_YAW_OUT_DQ 1 hour of data used to train filter Blue: Original, Red: Subtracted Data 5
Injections Injected 16 waveforms from the Murphy catalog (2009) and 128 waveforms from the Dimmelmeier catalog (2008) Each waveform injected at 10 evenly spaced intervals over a 24 hour period to explore entire antenna pattern. 1440 total injections. Two sets of PCs, Dimmelmeier and Murphy. 6 PCs for Dimmelmeier, 9 for Murphy 7
Dimmelmeier .2 kpc Original Data Filtered Data Data points: 1016 Avg Bdm = 2.7399e5 Correctly Identified: 1016 / 1016 (100%) Incorrectly identified waveforms: 0 / 1016 (0%) Undecided: 0 / 1016 (0%) Data points: 1063 Avg Bmd = 2.7481e5 Correctly Identified: 1063 / 1063 (100%) Incorrectly Identified: 0 / 1063 (0%) Undecided: 0 / 1063 (0%) 8
Murphy .2 kpc Original Data Filtered Data Data points: 128 Avg Bdm = 1.4e4 Correctly Identified: 112 / 128 (88%) Incorrectly identified waveforms: 15 / 128 (12%) Undecided: 1 / 128 (<1%) Data points: 145 Avg Bmd = 1.3663e4 Correctly Idenified: 127 / 145 (88%) Incorrectly Identified: 16 / 145 (11%) Undecided: 2 / 145 (1%) 9
Dimmelmeier 2 kpc Original Data Filtered Data Data points: 1090 Avg Bdm = 2.657e3 Correctly Identified: 1078 / 1090 (99%) Incorrectly identified waveforms: 0 / 1016 (0%) Undecided: 12 / 1090 (1%) Data points: 1153 Avg Bmd = 2.552e3 Correctly Identified: 1137 / 1153 (99%) Incorrectly Identified: 0 / 1153 (0%) Undecided: 16 / 1153 (1%) 10
Murphy 2 kpc Original Data Filtered Data Data points: 145 Avg Bdm = 115 Correctly Identified: 68 / 145 (47%) Incorrectly identified waveforms: 9 / 145 (6%) Undecided: 68 / 128 (47%) Data points: 145 Avg Bmd = 119 Correctly Idenified: 69 / 145 (48%) Incorrectly Identified: 11 / 145 (8%) Undecided: 65 / 145 (45%) 11
Dimmelmeier 10 kpc Original Data Filtered Data Data points: 1152 Avg Bdm = 96 Correctly Identified: 719 / 1152 (62%) Incorrectly identified waveforms: 0 / 1052 (0%) Undecided: 433 / 1152 (38%) Data points: 1153 Avg Bmd = 98 Correctly Identified: 719 / 1153 (62%) Incorrectly Identified: 0 / 1153 (0%) Undecided: 434 / 1153 (38%) 12
Murphy 10 kpc Original Data Filtered Data Data points: 145 Avg Bdm = -1.5 Correctly Identified: 7 / 145 (5%) Incorrectly identified waveforms: 16 / 145 (11%) Undecided: 122 / 145 (84%) Data points: 145 Avg Bmd = -1.32 Correctly Idenified: 7 / 145 (5%) Incorrectly Identified: 16 / 145 (11%) Undecided: 122 / 145 (84%) 13
Current/Next Steps Fix recoloring issues Study future detectors in depth Try Multi-Coherence method Examine other noise sources (LLO noise breathing, current LHO jitter, etc) Add new non-catalog waveforms 19
![Project Initiation Document for [Insert.Project.name] [Insert.Project.number]](/thumb/226757/project-initiation-document-for-insert-project-name-insert-project-number.jpg)
